Job Description
Are you ready to build the intelligent systems of tomorrow? Nexus Future Labs is seeking a visionary Senior AI/ML Engineer to join our elite team in San Francisco. We are on the cutting edge of Generative AI and Large Language Models (LLMs), and we need a technical leader who thrives in a fast-paced, high-impact environment.
In this role, you won't just write code; you will architect the neural networks that power the next generation of enterprise software. If you are passionate about pushing the boundaries of what's possible with AI and want to leave a legacy in the tech landscape leading up to 2026 and beyond, we want to meet you.
Why Join Us?
- Work with state-of-the-art technology (PyTorch, TensorFlow, Hugging Face).
- Competitive compensation and equity packages.
- Flexible remote-first culture with a vibrant San Francisco office.
- Opportunity to mentor junior engineers and shape our engineering culture.
Responsibilities
- Design, develop, and deploy scalable machine learning models and deep learning architectures.
- Optimize existing models for speed, accuracy, and resource efficiency to handle high-volume inference.
- Collaborate with cross-functional teams of data scientists, product managers, and engineers to define AI product requirements.
- Experiment with novel architectures and algorithms to push the performance limits of our NLP and Computer Vision capabilities.
- Ensure code quality, documentation, and best practices are maintained across the AI infrastructure.
- Lead technical discussions on AI ethics, bias mitigation, and model interpretability.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field (or equivalent professional experience).
- 5+ years of professional experience in software engineering with a strong focus on AI/ML.
- Expert proficiency in Python and major deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Strong understanding of NLP, LLMs (Transformers, GPT architectures), and RAG pipelines.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps practices.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.